Efficient Monte Carlo Simulation of the Delta Vector of a Bermudian Swaption in the LIBOR Market Model

Wilmott ◽  
2012 ◽  
Vol 2012 (62) ◽  
pp. 54-63
Author(s):  
Ralf Korn ◽  
Qian Ling
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Market Model ◽  
Libor Market Model

scholarly journals Fast and accurate exercise policies for Bermudan swaptions in the LIBOR market model

2016 ◽  
Vol 03 (01) ◽  
pp. 1650005 ◽  
Author(s):  
Patrik Karlsson ◽  
Shashi Jain ◽  
Cornelis W. Oosterlee
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Simulations ◽  
Upper Bound ◽  
Market Model ◽  
Monte Carlo Approach ◽  
Lower Upper ◽  
Libor Market Model ◽  
Bermudan Swaptions

This paper describes an American Monte Carlo approach for obtaining fast and accurate exercise policies for pricing of callable LIBOR Exotics (e.g., Bermudan swaptions) in the LIBOR market model using the Stochastic Grid Bundling Method (SGBM). SGBM is a bundling and regression based Monte Carlo method where the continuation value is projected onto a space where the distribution is known. We also demonstrate an algorithm to obtain accurate and tight lower–upper bound values without the need for nested Monte Carlo simulations.

MONTE CARLO SIMULATION OF VOLATILITY CLUSTERING IN MARKET MODEL WITH HERDING

1999 ◽  
Vol 02 (01) ◽  
pp. 83-94 ◽  
Author(s):  
DIETRICH STAUFFER ◽  
PAULO M. C. DE OLIVEIRA ◽  
AMERICO T. BERNARDES
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Root Mean Square ◽  
Cluster Size ◽  
Market Model ◽  
Mean Square ◽  
Trading Activity ◽  
Volatility Clustering

Through slow changes in the position of the traders, we introduce correlations between the volatility (root mean square change) of the prices at different times. We find this volatility correlation to decay slowly with time, as also observed in reality, and quite independent of the dimensionality of the lattice. We also make the trading activity of a cluster of traders proportional to the cluster size.

Monte Carlo market Greeks in the displaced diffusion Libor market model

2011 ◽  
Vol 14 (2) ◽  
pp. 23-37 ◽  
Author(s):  
Mark Joshi ◽  
Oh Kang Kwon
Keyword(s):  
Monte Carlo ◽  
Market Model ◽  
Libor Market Model

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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